1. Field of the Invention
This invention relates to an adaptive signal processing device, an echo suppressing device and a hand-portable telephone device. More particularly, it relates to an adaptive signal processing device, an echo suppressing device and a hand-portable telephone device configured to eliminate echo components.
2. Background of the Invention
In a satellite communication, submarine communication or a communication system employing a hand-portable telephone, an echo, that is an acoustic loop between a speaker and a microphone, may occur. Such echo not only deteriorates the quality of talk significantly, but invokes a feeling of alienation to the user.
Among known echo cancellation devices, there is a device in which transfer characteristics of an echo route looking from an installation station mounted in the hand-portable telephone are adaptively estimated to generate pseudo echo which then is subtracted from an echo-containing signal.
There is employed an adaptive filter having a so-called learning identification method and configured to sequentially estimate system parameters for adaptively estimating transfer characteristics. The portion of the cancellation device that corrects filter coefficients of the adaptive filter is called an adaptive algorithm.
A variety of adaptive algorithms for echo cancellation have hitherto been devised. Among the requirements for the adaptive algorithms are increased speed of convergence and execution and reduction in hardware size. In general, the better the convergence characteristics of the adaptive algorithm, the higher the processing quantity.
Among these adaptive algorithms, there is a least mean square (LMS) algorithm for correcting the filter coefficients to a minimum value based upon the acutest descent method. This adaptive algorithm has merit in that the least amount of processing operations suffices.
Another adaptive algorithm is the learning identification method which represents improvement of the LMS algorithm. This learning identification method is widely applied to products and put to practical use because of its superior converging characteristics.
It is known with the adaptive algorithm by the learning identification method that an operation of division in the adaptive algorithm needs to be executed from one speech sample to another. With the learning identification method, which represents improvement of the above-mentioned LMS algorithm, the quantity of residual echo may be diminished by its superior converging characteristics. However, as for the total quantity of processing operations, it is inferior to the LMS algorithm because of the necessity of executing division from one speech sample to another. Consequently, the load placed on the digital signal processor (DSP) mounted on a device implementing the learning identification method becomes significant.
In a hand-portable telephone employed in actual environments, echo estimation is delayed due to mixing of noise or the speech of the speaking party, thus significantly affecting converging characteristics of the echo cancellation device. The possible result is distortion of the speech of the speaking party on the side of the hand-portable telephone.